Classes

Class	Line #	Total Statements	Complexity	TOTAL Coverage	Actions
TreeBuilder	40	50	16	0.00%	Show methods

Class TreeBuilder

Class TreeBuilder	Line # 40	Total Statements 50	Complexity 16	TOTAL Coverage 0.00%
TreeBuilder(AlignmentViewport,ScoreModelI,SimilarityParamsI)   TreeBuilder(AlignmentViewport,ScoreModelI,SimilarityParamsI)	6161	12.012	2.02	0.0 0.00%
getSequences() : SequenceI[]   getSequences() : SequenceI[]	8787	1.01	1.01	0.0 0.00%
hasDistances() : boolean   hasDistances() : boolean	9696	1.01	1.01	0.0 0.00%
hasBootstrap() : boolean   hasBootstrap() : boolean	105105	1.01	1.01	0.0 0.00%
hasRootDistance() : boolean   hasRootDistance() : boolean	110110	1.01	1.01	0.0 0.00%
getLabels() : List<String>   getLabels() : List<String>	115115	1.01	1.01	0.0 0.00%
computeTree(ScoreModelI,SimilarityParamsI) : void   computeTree(ScoreModelI,SimilarityParamsI) : void	132132	7.07	1.01	0.0 0.00%
init(AlignmentView,int,int) : void   init(AlignmentView,int,int) : void	147147	14.014	4.04	0.0 0.00%
makeLeaves() : void   makeLeaves() : void	185185	11.011	3.03	0.0 0.00%
getOriginalData() : AlignmentView   getOriginalData() : AlignmentView	209209	1.01	1.01	0.0 0.00%

 

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1		/*
2		* Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
3		* Copyright (C) $$Year-Rel$$ The Jalview Authors
4		*
5		* This file is part of Jalview.
6		*
7		* Jalview is free software: you can redistribute it and/or
8		* modify it under the terms of the GNU General Public License
9		* as published by the Free Software Foundation, either version 3
10		* of the License, or (at your option) any later version.
11		*
12		* Jalview is distributed in the hope that it will be useful, but
13		* WITHOUT ANY WARRANTY; without even the implied warranty
14		* of MERCHANTABILITY or FITNESS FOR A PARTICULAR
15		* PURPOSE. See the GNU General Public License for more details.
16		*
17		* You should have received a copy of the GNU General Public License
18		* along with Jalview. If not, see <http://www.gnu.org/licenses/>.
19		* The Jalview Authors are detailed in the 'AUTHORS' file.
20		*/
21		package jalview.analysis;
22
23		import jalview.api.analysis.ScoreModelI;
24		import jalview.api.analysis.SimilarityParamsI;
25		import jalview.datamodel.AlignmentView;
26		import jalview.datamodel.BinaryNode;
27		import jalview.datamodel.CigarArray;
28		import jalview.datamodel.SeqCigar;
29		import jalview.datamodel.SequenceI;
30		import jalview.datamodel.SequenceNode;
31		import jalview.util.MessageManager;
32		import jalview.viewmodel.AlignmentViewport;
33
34
35		import java.util.ArrayList;
36		import java.util.BitSet;
37		import java.util.List;
38		import java.util.Vector;
39
		0% Uncovered Elements: 72 (72) Complexity: 16 Complexity Density: 0.32
40		public abstract class TreeBuilder extends TreeEngine
41		{
42		public static final String AVERAGE_DISTANCE = "AV";
43
44		public static final String NEIGHBOUR_JOINING = "NJ";
45
46		protected SequenceI[] sequences;
47
48		protected List<String> labels;
49
50		public AlignmentView seqData;
51
52		private AlignmentView seqStrings;
53
54		/**
55		* Constructor
56		*
57		* @param av
58		* @param sm
59		* @param scoreParameters
60		*/
		0% Uncovered Elements: 14 (14) Complexity: 2 Complexity Density: 0.17
61	0	public TreeBuilder(AlignmentViewport av, ScoreModelI sm,...
62		SimilarityParamsI scoreParameters)
63		{
64	0	int start, end;
65	0	boolean selview = av.getSelectionGroup() != null
66		&& av.getSelectionGroup().getSize() > 1;
67	0	seqStrings = av.getAlignmentView(selview);
68	0	if (!selview)
69		{
70	0	start = 0;
71	0	end = av.getAlignment().getWidth();
72	0	this.sequences = av.getAlignment().getSequencesArray();
73		}
74		else
75		{
76	0	start = av.getSelectionGroup().getStartRes();
77	0	end = av.getSelectionGroup().getEndRes() + 1;
78	0	this.sequences = av.getSelectionGroup()
79		.getSequencesInOrder(av.getAlignment());
80		}
81
82	0	init(seqStrings, start, end);
83
84	0	computeTree(sm, scoreParameters);
85		}
86
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
87	0	public SequenceI[] getSequences()...
88		{
89	0	return sequences;
90		}
91
92		/**
93		*
94		* @return true if tree has real distances
95		*/
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
96	0	public boolean hasDistances()...
97		{
98	0	return true;
99		}
100
101		/**
102		*
103		* @return true if tree has real bootstrap values
104		*/
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
105	0	public boolean hasBootstrap()...
106		{
107	0	return false;
108		}
109
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
110	0	public boolean hasRootDistance()...
111		{
112	0	return true;
113		}
114
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
115	0	public List<String> getLabels(){...
116	0	return this.labels;
117		}
118
119		/**
120		* Calculates the tree using the given score model and parameters, and the
121		* configured tree type
122		* <p>
123		* If the score model computes pairwise distance scores, then these are used
124		* directly to derive the tree
125		* <p>
126		* If the score model computes similarity scores, then the range of the scores
127		* is reversed to give a distance measure, and this is used to derive the tree
128		*
129		* @param sm
130		* @param scoreOptions
131		*/
		0% Uncovered Elements: 7 (7) Complexity: 1 Complexity Density: 0.14
132	0	protected void computeTree(ScoreModelI sm, SimilarityParamsI scoreOptions)...
133		{
134	0	labels = new ArrayList<String>();
135	0	sequences = sm.expandSeqData(sequences, seqData, scoreOptions, labels);
136	0	noseqs = sequences.length;
137
138	0	distances = sm.findDistances(seqData, scoreOptions);
139
140	0	makeLeaves();
141
142	0	noClus = clusters.size();
143
144	0	cluster();
145		}
146
		0% Uncovered Elements: 20 (20) Complexity: 4 Complexity Density: 0.29
147	0	protected void init(AlignmentView seqView, int start, int end)...
148		{
149	0	this.node = new Vector<BinaryNode>();
150	0	if (seqView != null)
151		{
152	0	this.seqData = seqView;
153		}
154		else
155		{
156	0	SeqCigar[] seqs = new SeqCigar[sequences.length];
157	0	for (int i = 0; i < sequences.length; i++)
158		{
159	0	seqs[i] = new SeqCigar(sequences[i], start, end);
160		}
161	0	CigarArray sdata = new CigarArray(seqs);
162	0	sdata.addOperation(CigarArray.M, end - start + 1);
163	0	this.seqData = new AlignmentView(sdata, start);
164		}
165
166		/*
167		* count the non-null sequences
168		*/
169	0	noseqs = 0;
170
171	0	done = new BitSet();
172
173	0	for (SequenceI seq : sequences)
174		{
175	0	if (seq != null)
176		{
177	0	noseqs++;
178		}
179		}
180		}
181
182		/**
183		* Start by making a cluster for each individual sequence
184		*/
		0% Uncovered Elements: 15 (15) Complexity: 3 Complexity Density: 0.27
185	0	void makeLeaves()...
186		{
187	0	clusters = new Vector<BitSet>();
188
189	0	for (int i = 0; i < noseqs; i++)
190		{
191	0	SequenceNode sn = new SequenceNode();
192
193	0	sn.setElement(sequences[i]);
194
195	0	if (labels.size() == noseqs)
196		{
197	0	sn.setLabel(labels.get(i));
198		}
199
200	0	sn.setName(sequences[i].getName());
201
202	0	node.addElement(sn);
203	0	BitSet bs = new BitSet();
204	0	bs.set(i);
205	0	clusters.addElement(bs);
206		}
207		}
208
		0% Uncovered Elements: 1 (1) Complexity: 1 Complexity Density: 1
209	0	public AlignmentView getOriginalData()...
210		{
211	0	return seqStrings;
212		}
213
214		}